Bin Chong — accepted AI-conference papers

2026

EchoEdit: Consistent Multi-Hop Question Answering via Ripple Control in Knowledge Editing

Jinwei Shi, Wenxuan Huang, Yu Xing, Yunhui Liu, Tao Zheng, Bin Chong +1

AAAI 2026technical

Knowledge editing aims to update specific knowledge in Large Language Models (LLMs) without retraining the entire model. However, existing methods generally struggle to manage the ripple effects of knowledge updates, particularly in multi-hop reasoning tasks, where conflicts between old and new info

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2026

On Modality Weighting and Specificity for Multi-Modal Entity Alignment

Yu Xing, Qizhuo Xie, Yunhui Liu, Qing Gu, Tao Zheng, Bin Chong +1

AAAI 2026technical

Multi-modal entity alignment aims to identify equivalent entities across different multi-modal knowledge graphs (MMKGs). While prior work has achieved notable progress through improved multi-modal encoding and cross-modal fusion techniques, two critical challenges remain unresolved. First, due to

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